To improve the estimation accuracy,
research has been devoted
to analyzing the characteristics of spectral distributions
and to incorporating these characteristics as prior information in the estimation.
Judd et al. analyzed the spectral distributions of daylight
and found that they can be written
as the sum of daylight's mean spectral distribution and
two other bases [1]}.
Jiang et al. proposed a camera-spectral-sensitivity estimation method
using prior information by which camera sensitivity can be approximated
by using two bases obtained by principal component analysis
on a set of spectral distributions of
28 camera sensitivities [2]}.
Jiang's method works better than the least-squares method.
However, its dedicated algorithm for incorporating
prior information makes the method specialized
only for camera sensitivity estimation.
